People’s behavior is often contingent on what other people are doing or have done. In dating and job markets, for example, each person’s choices limit what opportunities are available to others. A classic problem in sociology is explaining the relationship between individuals’ actions and larger-scale social patterns. My strategy is to use computer models of how people’s choices co-evolve with aspects of their environment—known as agent-based models (ABMs)—to determine what behavioral or demographic features are important for understanding social processes. I then use statistical models to assess to what degree these features exist in the real world. Substantively, most of my work examines the drivers of neighborhood segregation. More recently, I embarked on a study of how mate choice strategies shape (and are shaped by) dating, marriage, and affair markets.
With Fred Feinberg (UM Marketing and Statistics), I am also exploring how new data sources can be combined with choice models. The vast amounts of activity data from sources such as cell phones and the Internet make it possible to study human behavior with an unparalleled richness of detail. Such “big data” are interesting in large part because they are behavioral data that allow us to observe how people explore their environment, engage in novel or habitual behaviors, interact with others, and learn from past experiences. In ongoing work, we show how decision processes regarding mate choice can be extracted from online dating activity data.